2 unstable releases
0.2.0 | Mar 2, 2022 |
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0.1.0 | Nov 30, 2020 |
#11 in #done
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Used in cbdr
32KB
677 lines
A crate for testing whether the means of two Normal distributions are the same.
This crate implements Welch's t-test, an approximate solution to the Behrens-Fisher problem. The results are presented in the form of a confidence interval.
Example
Suppose we have a population distributed as X
(normal), and another
distributed as Y
(also normal, but possibly with different mean/variance to
X
). Let's take a sample from each population to estimate the difference
between the population means.
use behrens_fisher::*;
let x_sample: Vec<f64> = vec![1., 2., 3., 4.];
let y_sample: Vec<f64> = vec![3., 5., 7., 9., 11.];
let x_stats: SampleStats = x_sample.into_iter().collect();
let y_stats: SampleStats = y_sample.into_iter().collect();
let ci = difference_of_means(0.95, x_stats, y_stats).unwrap();
assert_eq!(ci.to_string(), "+4.50 ± 3.89 (p=95%)");
// Looks like μ[Y] > μ[X]!
Dependencies
~83KB